reproducibility

Hi everyone, I’m excited to wrap up the AutoAppendix project with our final findings and insights. Over the course of this initiative, we’ve worked to assess the reproducibility of artifacts submitted to the SC24 conference and create guidelines that aim to improve the standard for reproducible experiments in the future.

Reproducing and validating fixes for throttling bugs in HDFS improved system stability and performance.

Hello! I’m Joanna! I have been contributing to the ML in Detecting and Addressing System Drift project under the mentorship of Ray Andrew Sinurat and Sandeep Madireddy. My project aims to design a pipeline to evaluate drift detection algorithms on system traces.

Hello everyone! I’m Triveni, a Master’s student in Computer Science at Northern Illinois University (NIU). I’m excited to share my progress on the OSRE 2024 project Categorize Differences in Reproduced Visualizations focusing on data visualization reproducibility.

Background Hello there! I’m William and this is my final blog for my proposal “Developing A Comprehensive Pipeline to Benchmark Drift Management Approaches” under the mentorship of Ray Andrew Sinurat and Sandeep Madireddy under the LAST project.

Hello! In this blog post, I will explore a common issue in machine learning called data leakage, using an example from the paper: Benedetti, P., Perri, D., Simonetti, M., Gervasi, O.

The project aims to develop a service that facilitates the automated replication of COMPSs experiments within the Chameleon infrastructure

Introduction Hello everyone! I’m Ashwin Bardhwaj, an undergraduate student studying at UC Berkeley. As part of Micro Architecture Santa Cruz (MASC) my proposal under the mentorship of Jose Renau and Sakshi Garg looks to create a suite of benchmark programs for HDEval.

Hi, I am Mrigank. I am one of the Summer of Reproducibility fellows for 2024, and I will be working on deriving realistic performance benchmarks for Python interpreters with Ben Greenman from the University of Utah.

Hi, I am Mrigank. As a Summer of Reproducibility 2024 fellow, I am working on deriving realistic performance benchmarks for Python interpreters with Ben Greenman from the University of Utah. In this post, I will provide an update on the progress we have made so far.